Computer aided strategic planning

Abstract: Modelling concepts developed to analyse project strategic decisions have been extended and implemented in a computer system leading to a generalised methodology that allows modelling and evaluation of strategic decisions in almost any decision area. Some recent application areas of this modelling system are: strategic planning, evaluation of environmental policy impacts and evaluation of risks in owner contractor relationships . The system uses concepts of cross-impact analysis and probabilistic inference as the core of the analysis procedure. A modular model structure and a simplified knowledge acquisition procedure has been designed to avoid the excessive cognitive demands imposed to the users by the original cross-impact methodology. A simple questioning process is used to guide the discussion and elicit information in an ordered manner. The result is a powerful but easy to use computer modelling system where managers, or other potential users, are not exposed to the complexities of the mathematical model. The computer system is implemented in a Windows 95 platform and it provides a graphical interface to help the users in building a conceptual model for the decision problem. The model is a simplified structure of the variables and interactions that influence the decisions being analysed. Influences and interactions assessed by experts or decisions makers are stored in a knowledge base.
The system provides powerful analysis capabilities, such as: sensitivity analysis, to identify the most important variables in the decision problem; scenario analysis, to test decision under different environmental conditions; prediction of selected performance outcomes; risk analysis, to identify the risk involved in different alternatives; comparative analysis of the effects of alternative actions on individual or combined performance measures; explanatory capabilities through the model causal structure; etc. The computer model can translate expertise collected from multiple experts into a prediction of significant outcomes for decision-making. The model allows management to test different combinations of options and predict expected performance impacts associated with the decisions under analysis. The use of this decision-support tool can provide valuable insights on alternative options for strategic decision-making

Permission to reproduce these papers has been graciously provided by Royal Institute of Technology, Stockholm, Sweden. The assistance of the editors, Prof. Bo-Christer Björk and Dr. Adina Jägbeck, is gratefully appreciated.